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Global path guided model predictive path integral control: Applications to GPU-parallelizable robot simulation systems
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DOI：10.1016/j.compeleceng.2024.109645.png)
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Abstract
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In this paper, a global path guided model predictive path integral (Global-MPPI) control algorithmic framework is proposed, which integrates the model predictive path integral (MPPI) control with global path planning algorithms. The method is designed to address the challenges of robot path planning and execution in large-scale spaces with obstacles. It is applicable in both 2D and 3D spaces and can be implemented for both mobile robots and manipulators. To enhance practicality, we present an obstacle size expansion method aimed at minimizing collision risks. Validation of the algorithm is conducted using the advanced parallel physics simulator, IsaacGym, highlighting the effectiveness of the method in a randomly populated obstacle space. Multiple global path planning algorithms have been tested using Global-MPPI framework and the key factors affecting the effectiveness of the algorithms are analyzed. Furthermore, Global-MPPI is compared with recent algorithms solving similar problems. It can substantially increase the success rate when the right parameters are set.
Keywords:
Global path planning
Model predictive path integral (MPPI) control
Collision avoidance
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